TIME SERIES FORECASTING OF INTERMITTENT DEMAND BY USING ATA METHOD
نویسندگان
چکیده
منابع مشابه
Autoregressive Time Series Forecasting of Computational Demand
We study the predictive power of autoregressive moving average models when forecasting demand in two shared computational networks, PlanetLab and Tycoon. Demand in these networks is very volatile, and predictive techniques to plan usage in advance can improve the performance obtained drastically. Our key finding is that a random walk predictor performs best for one-step-ahead forecasts, whereas...
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Croston’s method is generally viewed as superior to exponential smoothing when demand is intermittent, but it has the drawbacks of bias and an inability to deal with obsolescence, in which an item’s demand ceases altogether. Several variants have been reported, some of which are unbiased on certain types of demand, but only one recent variant addresses the problem of obsolescence. We describe a...
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The inventory control of the products which have intermittent demand is essential for many organizations since these items have a low lead time demand but a high price. Since the intermittent demand pattern is irregular, the estimation of the lead time demand is challenging. A modified Markov chain model (MMCM) has been proposed for modeling and estimating intermittent demand data, motivated by...
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Intermittent demand or ID (also known as sporadic demand) comes about when a product experiences several periods of zero demand. Often in these situations, when demand occurs it is small, and sometimes highly variable in size. ID is often experienced in industries such as aviation, automotive, defence and manufacturing; it also typically occurs with products nearing the end of their life cycle....
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ژورنال
عنوان ژورنال: Mugla Journal of Science and Technology
سال: 2019
ISSN: 2149-3596
DOI: 10.22531/muglajsci.572444